Paper Info
Title
EDAS - Event-Disturbance Analysis System for Fossil Power Plants Operation
Abstract
A methodology for on-line diagnosis and prediction of power plant disturbances has been developed, implemented, and tested. The approach is sufficiently comprehensive to enable a wide variety of disturbances to be analyzed correctly and efficiently. The analysis is based on a novel knowledge representation, called Temporal Nodes Bayesian Networks (TNBN), a type of probabilistic network that include temporal information. A TNBN has a set of temporal nodes that represent state changes. Each temporal node is defined by a event and a time interval associated to its occurrence. The method has been implemented and integrated with a power plant training simulator. Disturbance models for the feedwater and superheater systems have been developed and implemented as the knowledge database for the disturbance analysis system.
Year
DOI
Venue
2000
10.1007/10720076_63
MICAI
Keywords
Field
DocType
fossil power plants operation,event-disturbance analysis system,bayesian network,knowledge representation,power plant
Brier score,EDAS,Data mining,Knowledge representation and reasoning,Computer science,Knowledge-based systems,Bayesian network,Artificial intelligence,Systems architecture,Knowledge base,Probabilistic logic,Machine learning
Conference
Volume
ISSN
ISBN
1793
0302-9743
3-540-67354-7
Citations 
PageRank 
References 
0
0.34
2
Authors
2
Name
Order
Citations
PageRank
Gustavo Arroyo-Figueroa117022.16
Luis Enrique Sucar232.12